Cosmic sound [Elektronische Ressource] : measuring the Universe with baryonic acoustic oscillations / angefertigt von Gert Hütsi

Gert Hütsi

Sujets

• Astronomie

Informations

• Publié par: ludwig-maximilians-universitat_munchen
• Publié le: 01 janvier 2006
• Nombre de lectures: 10
• Langue: English
• Poids de l'ouvrage: 6 Mo

Extrait

Cosmicsound: MeasuringtheUniverse
withbaryonicacousticoscillations
Dissertation
derFakultätfürPhysikder
Ludwig Maximilians UniversitätMünchen
angefertigtvon
GertHütsi
ausTallinn(Estland)
München,den1. März2006GertHütsi:
Cosmicsound: MeasuringtheUniversewithbaryonicacousticoscillations
DissertationderFakultätfürPhysikderLudwig Maximilians UniversitätMünchen
ausgeführtamMax Planck InstitutfürAstrophysik
1. Gutachter: Prof. Dr. RashidSunyaev,MPAGarching
2. Prof. Dr. ViatcheslavMukhanov,LMUMünchen
TagdermündlichenPrüfung: 30. Mai2006Contents
1. Introduction 3
1.1. StandardModelofcosmology . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1.1. Homogeneous isotropicbackgrounds. Classicalcosmologicaltests . . . 4
1.1.2. PerturbedFLRWmodels . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.2. Introductiontoacousticoscillations . . . . . . . . . . . . . . . . . . . . . . . . 13
1.3. Cosmologicalparameters. MarkovChainMonteCarlo . . . . . . . . . . . . . . 18
1.4. Largegalaxy/clustersurveys. Fastsemianalyticalmethodsforstructureformation 21
1.5. InthisThesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2. Clustering of SZ clusters on a past light cone: acoustic oscillations and con
straintsondarkenergy 31
2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.2. Light conepowerspectrumofgalaxyclusters . . . . . . . . . . . . . . . . . . . 33
2.2.1. ClusterpowerspectrafromVIRGOsimulations . . . . . . . . . . . . . . 34
2.2.2. Comparisonwiththeanalyticaldescription: accuracyofthebiasingscheme 41
2.3. SZclustersandbaryonicoscillations . . . . . . . . . . . . . . . . . . . . . . . . 43
2.3.1. SZ selectedclusters. Mass observablerelations . . . . . . . . . . . . . . 46
2.3.2. Accuracyofthepowerspectrumdetermination . . . . . . . . . . . . . . 47
2.3.3. Prospectsofdetectingbaryonic“wiggles”. ComparisonwithSDSSLRG 50
2.3.4. SomeremarksonSZvs. opticalclusterselection . . . . . . . . . . . . . 53
2.4. ConstraintsonDarkEnergy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
2.4.1. 2Dpowerspectrumonalight cone . . . . . . . . . . . . . . . . . . . . 54
2.4.2. Parameterestimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
2.5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3. Acoustic oscillations in the SDSS DR4 Luminous Red Galaxy sample power
spectrum 65
3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.2. Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.3. Powerspectrumcalculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.4. Powererrorsandcovariancematrix . . . . . . . . . . . . . . . . . . . 73
3.5. Relationtothetruespectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
3.6. Modelspectra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
3.7. Determinationoftheacousticscale . . . . . . . . . . . . . . . . . . . . . . . . . 81
3.8. Correlationfunctionanalysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
3.9. Comparisonwiththeothersurveys . . . . . . . . . . . . . . . . . . . . . . . . . 85
3.10. DiscussionandConclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
iContents
4. PowerspectrumoftheSDSSluminousredgalaxies: constraintsoncosmolog
icalparameters 89
4.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.2. Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4.3. Powerspectrum/acousticscaletransformation . . . . . . . . . . . . . . . . . . 92
4.4. Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.4.1. W+HSTdata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.4.2. Constraintsfromthemeasurementoftheacousticscale . . . . . . . . . . 102
4.4.3.fromthefullpowerspectrum . . . . . . . . . . . . . . . . . 107
4.4.4. Onedimensionaldistributions . . . . . . . . . . . . . . . . . . . . . . . 107
4.4.5. Mostinterestingconstraints . . . . . . . . . . . . . . . . . . . . . . . . 108
4.5. DiscussionandConclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
5. Conclusions 117
A. Fittingformulaefortheacousticscales 119
B. Testproblem 123
C. Mockcatalogs 125
D. Powerspectrumfromthehalomodel 131
E. Fittingformulaeforthecouplingkernels 133
F. Nonlinearmodelfitting. Correlateddata 135
G. Goodnessoffit. CorrelatedGaussiandata 137
H. SDSSLRGpowerspectrumandcovariancematrix 139
Bibliography 141
iiAbstract
During the last ten to fifteen years cosmology has turned from a data starved to a data driven
science. Several key parameters of the Universe have now been measured with an accuracy
better than 10%. Surprisingly, it has been found that instead of slowing down, the expansion of
the Universe proceeds at an ever increasing rate. From this we infer the existence of a negative
pressure component– the so called Dark Energy (DE)– that makes up more than two thirds of
the total matter energy content of our Universe. It is generally agreed amongst cosmologists
and high energy physicists that understanding the nature of the DE poses one of the biggest
challengesforthemoderntheoreticalphysics.
Future cosmological datasets, being superior in both quantity and quality to currently existing
data, hold the promise for unveiling many of the properties of the mysterious DE component.
With ever larger datasets, as the statistical errors decrease, one needs to have a very good con
trol over the possible systematic uncertainties. To make progress, one has to concentrate the
observational effort towards the phenomena that are theoretically best understood and also least
“contaminated” by complex astrophysical processes or several intervening foregrounds. Cur-
rentlybyfarthecleanestcosmologicalinformationhasbeenobtainedthroughmeasurementsof
theangulartemperaturefluctuationsoftheCosmicMicrowaveBackground(CMB).Thetypical
angularsizeoftheCMBtemperaturefluctuationsisdeterminedbythedistancethesoundwaves
in the tightly coupled baryon photon fluid can have traveled since the Big Bang until the epoch
of recombination. A similar scale is also expected to be imprinted in the large scale matter dis
tributionastracedby,forinstance,galaxiesorgalaxyclusters. Measurementsofthepeaksinthe
CMB angular power spectrum fix the physical scale of the sound horizon with a high precision.
By identifying the corresponding features in the low redshift matter power spectrum one is able
toputconstraintsonseveralcosmologicalparameters.
Inthisthesiswehaveinvestigatedtheprospectsforthefuturewide fieldSZclustersurveysto
detect the acoustic scale in the matter power spectrum, specifically concentrating on the possi
bilities for constraining the properties of the DE. The core part of the thesis is concerned with
a power spectrum analysis of the SDSS Luminous Red Galaxy (LRG) sample. We have been
able to detect acoustic features in the redshift space power spectrum of LRGs down to scales
−1of ∼ 0.2hMpc , which approximately corresponds to the seventh peak in the CMB angular
spectrum. Using this power spectrum measurement along with the measured size of the sound
horizon, we have carried out the maximum likelihood cosmological parameter estimation us
ing Markov chain Monte Carlo techniques. The precise measurement of the low redshift sound
horizon in combination with the CMB data has enabled us to measure, under some simplifying
+1.9assumptions,theHubbleconstantwithahighprecision: H = 70.8 km/s/Mpc. Alsowehave0 −1.8
shown that a decelerating expansion of the Universe is ruled out at more than 5σ confidence
level.
1Contents
21. Introduction
CosmologyisthestudyoftheoriginandevolutionofourUniverseandassuchithasfairlyambi
tioustasks. Overthelast10 15years,duetotherapiddevelopmentofobservationalcosmology,
our knowledge about the Universe has increased dramatically. One can say that has
turnedfromadata starvedtoadata drivenscience. SeveralkeyparametersofourUniversehave
beenmeasuredtoanaccuracybetterthanafewpercent. Moreover,wehaveenteredastagewhere
wecanstartmakingaccuratetestsformanyoftheunderlyingassumptions. Thissuccesshasled
to the establishment of the Standard Model of cosmology, often also called the “Concordance”
Model, in order to avoid confusion with the Standard Model of particle physics. Although it
is very successful in explaining the great body of diverse observational data (and that with the
model having in its simplest form only 5 6 free parameters!), we have to be worried about the
doubly occurring word “Dark”, which probably also adequately describes our current level of
knowledge. According to current best estimates, approximately two thirds of our Universe is
made up of the mysterious smoothly distributed Dark Energy (DE) component with negative
pressure,aboutone thirdisintheformofthepressurelessandnoninteractingColdDarkMatter
(CDM),whilethefamiliarbaryonicmattermakesuplessthan5%ofthetotaldensity. Although
wehavenotyetdetectedparticlespossiblymakinguptheCDMthereareaplentyofcandidates
providedbythevariousextensionsoftheStandardModelofparticlephysics. ConcerningtheDE
thesituationismuchlesssatis